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venv/lib/python3.10/site-packages/edgar/funds/thirteenf.py

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+"""
+13F filing module for investment funds.
+
+This module provides classes and functions for working with 13F filings
+that report investment fund portfolio holdings.
+"""
+import logging
+
+import pandas as pd
+
+# Define constants
+THIRTEENF_FORMS = ['13F-HR', "13F-HR/A", "13F-NT", "13F-NT/A", "13F-CTR", "13F-CTR/A"]
+
+log = logging.getLogger(__name__)
+
+# We'll define these functions without directly importing them at the module level
+# to avoid circular imports
+
+def get_ThirteenF():
+    """Dynamically import ThirteenF to avoid circular imports."""
+    from edgar.thirteenf import ThirteenF as OriginalThirteenF
+    return OriginalThirteenF
+
+# Create property-like functions that provide lazy loading
+def ThirteenF():
+    """Get the ThirteenF class, dynamically importing it to avoid circular imports."""
+    return get_ThirteenF()
+
+def get_thirteenf_portfolio(filing) -> pd.DataFrame:
+    """
+    Extract portfolio holdings from a 13F filing.
+
+    Args:
+        filing: The 13F filing to extract data from
+
+    Returns:
+        DataFrame containing portfolio holdings
+    """
+    try:
+        # Create a ThirteenF from the filing
+        thirteenf_class = get_ThirteenF()
+        thirteenf = thirteenf_class(filing, use_latest_period_of_report=True)
+
+        # Check if the filing has an information table
+        if not thirteenf.has_infotable():
+            log.info("Filing %s does not have an information table", filing.accession_no)
+            return pd.DataFrame()
+
+        # Extract the information table
+        infotable = thirteenf.infotable
+        if infotable is None:
+            log.warning("Could not extract information table from filing %s", filing.accession_no)
+            return pd.DataFrame()
+
+        # Convert to DataFrame
+        df = pd.DataFrame(infotable)
+
+        # Clean up and organize data
+        if not df.empty:
+            # Update column names for consistency
+            if 'nameOfIssuer' in df.columns:
+                df = df.rename(columns={
+                    'nameOfIssuer': 'name',
+                    'titleOfClass': 'title',
+                    'cusip': 'cusip',
+                    'value': 'value_usd',
+                    'sshPrnamt': 'shares',
+                    'sshPrnamtType': 'share_type',
+                    'investmentDiscretion': 'investment_discretion',
+                    'votingAuthority': 'voting_authority'
+                })
+
+            # Add ticker mapping if possible
+            try:
+                from edgar.reference import cusip_ticker_mapping
+                cusip_map = cusip_ticker_mapping(allow_duplicate_cusips=False)
+                df['ticker'] = df['cusip'].map(cusip_map.Ticker)
+            except Exception as e:
+                log.warning("Error adding ticker mappings: %s", e)
+                df['ticker'] = None
+
+            # Calculate percent of portfolio
+            if 'value_usd' in df.columns:
+                total_value = df['value_usd'].sum()
+                if total_value > 0:
+                    df['pct_value'] = df['value_usd'] / total_value * 100
+                else:
+                    df['pct_value'] = 0
+
+            # Sort by value
+            df = df.sort_values('value_usd', ascending=False).reset_index(drop=True)
+
+        return df
+
+    except Exception as e:
+        log.warning("Error extracting holdings from 13F filing: %s", e)
+
+    # Return empty DataFrame if extraction failed
+    return pd.DataFrame()
+
+# Functions for export
+__all__ = [
+    'ThirteenF',
+    'THIRTEENF_FORMS',
+    'get_thirteenf_portfolio',
+]